Triple
T14808620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tom Hanks as Scott Turner |
E348108
|
entity |
| Predicate | worksInSetting |
P115811
|
FINISHED |
| Object | small town |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: small town | Statement: [Tom Hanks as Scott Turner, worksInSetting, small town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worksInSetting Context triple: [Tom Hanks as Scott Turner, worksInSetting, small town]
-
A.
worksWhen
Indicates that one entity functions or operates correctly only under the conditions or context defined by another entity.
-
B.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
C.
worksAs
Indicates that an entity performs the role, job, or occupation specified by another entity.
-
D.
worksThrough
Indicates that one entity performs an action, causes an effect, or achieves a result by using, employing, or acting via another entity as an intermediary or means.
-
E.
worksOnProgram
Indicates that an entity is actively involved in contributing effort or performing tasks on a particular program.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decf33b6a08190ab6a4cfeda2cc09c |
completed | April 14, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69de8c0ef8a4819092d84478b1f56db1 |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:45 a.m.